Monitoring and Modelling of Water Quality

zones in two or three dimensions in heterogeneous, anisotropic porous media or fractured media. Model simulates convection, dispersion, diffusion, adsorption, desorption, and microbial processes based on oxygen-limited, anaerobic, first-order, or Monod-type biodegradation kinetics as well as anaerobic or first-order sequential degradation involving multiple daughter species.

wastewater.The UWWT Directive is related to collection, treatment and discharge of urban wastewater.It also aims to protect the environment from the negative influence of the disposal/discharge of insufficiently treated urban wastewater.The directive encompasses four activities related to wastewater management: planning, regulation, monitoring, and information and reporting.Monitoring requires ensuring (Quevauviller et al., 2006): • appropriate monitoring capacity of parameters to be monitored; • accurate analysis of samples by using standard methods; • timely frequency of monitoring for: monitoring of discharges from urban wastewater treatment plants; and monitoring of waters receiving those discharges.
The Nitrates Directive's main objective is to protect water quality across Europe by eliminating the jeopardy of nitrates pollution and byagricultural practices.All Member States have to examine water with regard to nitrate concentrations and trophic state.Hence, good monitoring procedures and networks are crucial in executing the acts of the Directive.
There are currently 31 000 groundwater sampling sites in the EU, and 27 000 surface water stations.There are differences between countries in the designing and using their monitoring networks.This may be due to the fact that there are no specific official guidelines and/or protocols in the European Union (Fraters et al., 2003).On the other hand, the existing (in a draft form) guidelines for monitoring under the Nitrates Directive outline the monitoring of both agriculture (nutrient balances, changes in land usage and manure storage capacity) and water quality (effects of nitrate input to surface water and groundwater).
EC Shellfish Waters Directive (SWD, 2006) aims to protect shellfish populations.Hence it specifies the way how shellfish water should be monitored throughout the year.The frequency of sampling depends on the importance of the parameter being measured.The parameters encompass physico-chemical indicators including toxic organic and metal contaminants.
In Poland, the obligatory examinations of surface water and evaluation of its quality is enclosed in "Water Law" act (Water Law Act, 2010).In turn, the operating range, procedures and criteria of the quality's evaluation might be found in several regulations concerning: habitat requirements for fishwater, extinguishing of water vulnerable for nitrates pollution, standards for drinking water derived from surface resources, classification of surface water status and types and procedures of surface water monitoring.
The aim of the surface water monitoring is the establishment of basis for further activities which should improve the status of water.These actions include also the prevention from pollution, especially the elimination of the eutrophication process.The holistic assessment of the surface water condition is the main tool of water resources management within the river basins, which stand for the cardinal units in water policy.
The legal basis of groundwater monitoring constitutes two acts: "Environmental Protection" (Environmental Protection Act, 2001) and "Water Law" acts.Similarly to surface water monitoring, the detailed description of procedures and performance might be found in a set of regulations concerning: extinguishing of water vulnerable for nitrates pollution, criteria and methods of the groundwater status evaluation and forms and procedures for carrying out monitoring of surface and groundwater bodies.The monitoring actions are directed towards the creation of an information base including chemical condition of groundwater within outlined bodies.The continuous control of groundwater quality aims at further planning of both clean-up activities and a protection from pollution, which leads to achieve good groundwater status before the date set by the European Commission.

Monitoring of surface water quality in Poland
The "Water Law" act introduced a division of the state area into water basins and water regions; initially, there were two main areas of water basins -the Vistula and the Oder river basins.Amendment to the Water Law act from 2005 introduced eight new water basins, which replaced the initial two (Inspectorate of Environmental Protection, 2010).
In case of examinations and evaluations of surface water quality based on monitoring, years 2010-2012 are the first period of a six-year-long project of water management within outlined water bodies.During this time, monitoring of surface water quality is performed in three types of activities: surveillance/diagnostic, operational and investigative/research.Fist mentioned aims to provide general assessment of water quality for each catchment and sub-catchment within the whole river basin.Information gathered during this type of research enables the determination of long-term changes in natural conditions.Second one, operational monitoring is carried out within those homogenous water bodies which, during the diagnostic phase, were described as endangered of failure to achieve the good status.This monitoring aims at evaluation of changes following the implementation of repair programmes.The last type -research monitoring -aims at observation and describing of unrecognised threats of pollution within surface water bodies.
In case of surface water monitoring, there are ten types of sampling/monitoring points: diagnostic (MD), operational (MO), operational for water vulnerable to nitrates pollution (MORO), operational for water exposed to eutrophication (MOEU), operational for fishwater (MORY), operational for surface water abstracted for public water supply (MOPI), operational for water qualified as recreational (MORE), operational for water bodies in boundaries of which there are protected ecosystems strictly dependent on quality of water (MONA), operational related to the execution of the international agreements (MOIN), research (MB).
The range and the frequency of monitoring depend on the type of monitoring points.For the diagnostic points, the frequency of measurements is from 1 to 8 times a year for biological factors and from 1 to 12 times a year for physic-chemical parameters.For the operational monitoring points the range of measured parameters depends on the type of pressure put on the environment within water bodies.In case of units in which effluents/discharges hazardous substances, especially priority hazardous substances were observed, or in monitoring points where the amount of these substances exceeded permissible limits, the monitoring is performed annually.For other operational monitoring points the frequency of examinations is once in 3 years for fishwater and once in a year in case of surface water used for public water supply.
The key role in the monitoring system play points located in estuaries of big rivers and those flowing directly to the Baltic Sea.In these places, the frequency of sampling is not less than 12 times a year and the range of parameters being examined include heavy metals, biogenic substances and indicators describing the oxygen conditions.
Each year the evaluation of surface water status is made for water bodies which were included in the diagnostic monitoring.In year 2013, after finishing the entire diagnostic programme, the summary specification of the status within surface water bodies will be prepared.On the basis of that, using the extrapolation method, the rest of the water bodies which are not included in the diagnostic monitoring will be assessed.The scheme of evaluation of surface water status is presented on figure below (Fig. 1).The evaluation of the chemical status of water included in the operational monitoring depends on the type of ongoing programmes.In any case, the classification of ecological status is made on the basis of the limited number of factors depending on the potential threats of pollution and pressure put on the water environment by anthropogenic discharges.Hence, the evaluation of surface water status is fraught with uncertainties and rather informs about the success or failure in the implementation of repair programmes than about real conditions of the environment.

Monitoring of groundwater quality in Poland
On a national scale, the institution responsible for monitoring of groundwater is Polish Hydrogeological Survey (PSH).Their tasks are performed by the Polish Geological Institute.These tasks include (Sadurski 2005): • performing hydrogeological measurements and observations; • collecting and processing the data concerning groundwater condition and resources available, • performing current analyses and assessments of hydrogeological situation; • compiling and forwarding to the appropriate administration authorities, the forecasts of the changes in both resources and quality of groundwater, and about threats of pollution; • compiling and forwarding to the public administration warnings about dangerous phenomena occurring in recharge zones and groundwater intakes.
Examinations of the groundwater quality are carried out within groundwater bodies defined as "determined volume of groundwater occurring within an aquifer or aquifers".This term refers to the functioning in Polish hydrogeology term "free water occurring in the saturation zone" (Pazdro 1977).
The delineation of groundwater bodies was made taking into consideration various factors, such as circulation conditions (i.e.locations of recharge and drainage zones), administrative and hydrological boundaries (catchments, basins), lithology and stratigraphy of water-bearing rocks.Groundwater bodies are complex structures, they might consist of few water horizons.
Measurements of the ground water quality are carried out within the national observationalresearch network.This network was designed to evaluate the groundwater status and to determine trends in chemical changes.Monitoring actions are performed for both the qualitative and quantitative assessment of the groundwater.The latter one is embraced by diagnostic, operational and research monitoring.The density of observation points reflects the complexity of geological and hydrogeological conditions and natural and anthropogenic pressures put on the water quality.Additional attention in monitoring is paid to areas around national boundaries and to protected areas.Hence, the final location of points depends on the formulated aim of monitoring, and the network comprises of (Fig. 2):  Diagnostic monitoring aim is to determine anthropogenic impacts on the groundwater quality as well as the long-term trends in chemical status changes.Accordingly, the changes might be induced by natural processes and human activities.The results of this type monitoring actions help to design the further operational monitoring system.Parameters examined during the diagnostic phase of groundwater monitoring are: pH, TOC (total organic carbon), conductivity, temperature, DO (dissolved oxygen), ammonia, arsenic, nitrates, barium, boron, chloride, chromium, zinc, fluoride, phosphates, aluminium, cadmium, magnesium, manganese, copper, nickel, lead, potassium, sulphate, sodium, calcium, carbohydrates, iron, organic substances: AOX -adsorbed organochlorine compounds.The range of parameters might be extended by substances expected to be present in groundwater regarding the potential pollution sources.
Operational monitoring should provide data necessary to reach the proper level of certainty in classifying groundwater endangered by not reaching the good quality status.The second major aim is to identify upwards trends in the chemical composition which might indicate the pollution, especially human-induced.The range of measured parameters includes: temperature, conductivity, pH, DO, ammonia, nitrites, nitrates, chloride, sulphate, phosphates, bicarbonates, sodium, potassium, calcium, magnesium, manganese and iron.In addition, if some parameters measured in the diagnostic phase of monitoring, classified the groundwater status as poor or bad, they are also included into operational observations.
Research monitoring aims at extending the recognition achieved after two previous phases of monitoring.This type of researches leads to determine the reasons, sizes and influences of the accidental pollution.This monitoring might be performed for those groundwater bodies which might not achieve the good quality status by the fixed date, and which are not subjected to the operational actions (Kazimierski & Pilchowska-Kazimierska, 2006).
There are 5 classes of groundwater quality: IV class -water of non-satisfactory quality.Values of some parameters are significantly increased as a result of natural or human-induced processes, • V class -water of bad quality.Chemical composition of this type of water confirms the predominant human impact.
Classes from I to III stand for good status of groundwater, whereas classes IV and V -bad status.The status of groundwater bodies is presented on the maps in a following way: area filled with green colour -good status, area filled with red colour -bad status and black points -observed trends in chemical composition of groundwater (example on Fig. 3).
Fig. 3.The classification of groundwater status in year 2009: green colour stands for the good status of groundwater, red for bad status, light green and orange represent a high uncertainty of obtained results (source: http://www.gios.gov.pl) The frequency of chemical examinations depends on both type of monitoring and type of aquifer.In case of unconfined aquifer the frequency is one time in 3 years (diagnostic monitoring) or twice a year (operational monitoring).On the other hand, in case of deeper aquifers, which are characterised by piezometric surface, the frequency is once in 6 years (diagnostic monitoring) or once a year (operational monitoring).
Results obtained during the monitoring are widespread via different publications, such as Quarterly Bulletin of Groundwater.Results are also gathered in databases, e.g.: • SOH (Hydrogeological Observations System).This database collects information about water table level fluctuations (every Monday) and chemical condition (every year).
• MONBADA (MONitoring DataBAse) is the database of National Environmental Monitoring.It was created in 1991.In MONBADA data regarding the chemical status of groundwater and its evaluation are gathered.On the basis of collected results annual reports are prepared.These reports are published in series "Library of Environmental Monitoring" and on the National Monitoring web site (http://www.gios.gov.pl/wodypod).

Monitoring of precipitation in Poland
Qualitative monitoring of precipitation in terms of its chemical composition and occurrence of the acidic atmospheric deposition has been largely studied in different sites and locations in Central and Western Europe, North America and East Asia, during the last years (Kulshrestha et al., 2009;Li et al., 2007;Menz & Seip, 2004;Tsitouridou & Anatolaki, 2007;Wang et al., 2000).
In Poland, the National Chemistry Monitoring of Precipitation and Assessment of Pollutants Deposition were established in 1998 as a subsystem of National Environmental Monitoring.
Monitoring tests in the full annual cycle were carried out for the first time in 1999.The Institute of Meteorology and Water Management in Wroclaw carried substantive supervision over implementation of these tasks.The purpose of monitoring of the precipitation chemistry and of the deposition of pollutants is to define, at a national scale, spatial and temporal decomposition of pollutants entering from the wet precipitation to the ground.National network of measurement -monitoring consists of: 25 research stations (to ensure the representativeness of precipitation chemistry measurements) and 162 rainfall stations (which characterise the average rainfall for the Poland area).At all 25 research stations the rainwater is collected continuously and analysed on a monthly basis.At the time of sampling, the amount and type of precipitation are measured.Monthly precipitation samples are analysed for the concentration of acidic compounds, nutrients and metals (including heavy metals).The monitoring includes: chlorides, sulphates, nitrites and nitrates, ammonia nitrogen, total nitrogen, total phosphorus, potassium, sodium, calcium, magnesium, zinc, copper, iron, lead, cadmium, nickel, chromium and manganese.Measurements include also pH and electrical conductivity of the precipitation.Basing on the results from all monitoring stations (25 research and 162 rainfall stations) maps of wet deposition of monitored substances are prepared.
The atmospheric precipitation collectors are characterised by a different degree of automation; the most sophisticated can record meteorological data and also some characteristics of precipitation (rate, electrolytic conductivity, pH) (Chief Inspectorate of Environmental Protection, National Chemistry Monitoring of Precipitation and Assessment of Pollutants Deposition, http://www.gios.gov.pl/chemizm/index.html.)The simplest collectors for total precipitation sampled for chemical analysis are glass, metal, and plastic containers.The containers are equipped with glass, steel, or polyethylene funnels.Figure 4 presents the scheme of the simplest collector (Bijsman et al., 1991).The more complicated version has an automatic cover and a humidity sensor; in this type of system dry precipitation is excluded from a sample (Fig. 5) (Ligocki et al., 1985).ISO 5667-8:1993(ISO, 1993).
Collection of atmospheric precipitation has to satisfy a number of conditions, especially with respect to a collection system.In compliance with recommendations of the European Monitoring Environmental Program (EMEP) the collectors for wet precipitation and total precipitation should be characterised by: • the sampler should not be too large or bulky, because this will obstruct the air flow around the sampler; the diameter of the collector must be large enough to provide samples large enough for chemical analysis -a diameter of 20 cm is sufficient; www.intechopen.com Water Quality Monitoring and Assessment

200
• collector must be made of a material, which does not alter the chemical composition of the sample, and shall give a reliable measure of the amount of precipitation on a daily basis; • an appropriate container capacity to avoid any loss of a sample even when precipitation is very intensive.

Water quality modelling
Mathematical model is described in different ways.The encyclopaedia of life support system described a model as an approximate description of a class of real-world objects and phenomena expressed by mathematical symbolisms (Agoshkov, 2002).Concise Oxford Dictionary (1990) described a model as a simplified form of a system that assists calculations and predictions of a condition of a system in a given situation.The United States Environmental Protection Agency USEPA (EPA, 2009) described water quality models as tools for simulating the movement of precipitation and pollutants from the ground surface through pipe and channel networks, storage treatment units and finally to receiving waters (Kannel et al., 2011).
Model predictions might be used in addition to or instead of monitoring data for several reasons:

•
Modelling might be feasible in some situations where monitoring is not.
• Integrated monitoring and modelling systems could provide better information than one or the other alone for the same total cost.

•
For example, regression analyses that correlate pollutant concentration with some more easily measurable factor (such as streamflow) could be used to extend monitoring data.Models can also be used in a Bayesian framework to determine preliminary probability distributions of impairment that can help direct monitoring efforts and reduce the quantity of monitoring data needed for making decisions.

•
Modelling can be used to assess (predict) future water quality situations resulting from different management strategies.For example, assessing the improvement in water quality after a new wastewater treatment plant is built, or the effect of increased industrial growth and effluent discharges (UNESCO, 2005).
Water quality modelling for decision-making occurs at a disciplinary divide between science and management.Workers in science and management operate in fields that traditionally have different objectives, priorities and expectations.These differences can create barriers to the effective use of scientific models by watershed managers (McNamara, 2004).
Water quality models include both mathematical expressions and expert scientific judgement.They include process-based (mechanistic) models and data-based (statistical) models.The models should be characterised by following features: • link management options to meaningful response variables (such as pollutant sources and water quality standard parameters), • incorporate the entire chain from stressors to responses, • be consistent with scientific theory, • have reported the uncertainty, www.intechopen.com Monitoring and Modelling of Water Quality

201
• compatible with the quantity and quality of available data (The use of complex mechanistic models for water quality prediction in situations with little useful water quality data does not compensate for that lack of data.Model complexity can give the impression of credibility, but this is usually misleading).
It is often preferable to begin with simple models and then, over time, add additional complexity as justified by the collection and analysis of additional data.This strategy makes efficient use of resources.It targets the effort toward information and models that will reduce the uncertainty as the analysis proceeds (UNESCO, 2005).
Water quality models can be applied to many different types of water system, including atmospheric water, groundwater, wetlands, streams, rivers, lakes, reservoirs, estuaries, coastal waters and oceans.
The fact that most, if not all, water quality models cannot accurately predict what actually happens does not detract from their value.Even relatively simple models can help managers understand the real world prototype and estimate at least the relative, if not actual, change in water quality associated with given changes in the inputs resulting from management policies or practices (UNESCO, 2005).

Tools for water quality modelling -Examples and purposes of use
Models simulating water quality are used for three main purposes: • Planning remediation of degraded areas or protection of water resources, soils, health and ecosystems.
In this case models calculate results of different scenarios.This type of models answers "what if" question and finds the solution which is best according to a specified objective and satisfying physical, technical, legal and other constraints (Wagner, 1992).
Groundwater quality models can analyse possibilities for removing a plume of polluted water or control its flow away from wells, streams, lakes.For such purpose models can simulate scenarios including: inserting curtain walls, removing polluted soil, in situ (bio)chemical remediation or installing pumping/recharge wells (Wagner, 1992).For surface waters this type of models is used for development of long-time management scenarios for river basins or lakes and for assessment of the results of planned land use changes and investments (Kardaetz et al., 2008;Thebault & Qotbi, 1999;Yoshimura et al., 2009).Models of this type for atmospheric water quality are used widely to predict the impact of pollutants emissions on the eutrophication and acidification processes.For all types of water (including water distribution networks and wastewater collecting systems) models can be used also for planning better and cost-effective monitoring and controlling systems.
• Simulating ongoing processes using real-time modelling systems.Real-time refers to a state where data referring to a system is analysed and updated at the rate at which it is received (i.e. at the rate at which the system operates).Real-time modelling (also referred to as online modelling) refers to the process of employing numerical models to make predictions about current or near future system states and outputs based on newly received (and forecasted) data.Real-time modelling is employed in a range of environmental fields, including meteorology, hydrology, and in urban water systems (UWS), typically for one of the following purposes (Hutton et al., 2010): Water Quality Monitoring and Assessment

202
• To provide warnings of future events, • To inform management of future system states and potential anomalies, • To explore a range of possible control strategies such that the control solution that optimises some function is implemented (typically a system property such as: combined sewer overflows discharge, operational cost, surface water intakes management or groundwater in-situ remediation processes).
• Analysing past events.This type of models is used for example when there is a need for information about: • Influence of historical human activities or natural processes (as climate changes) on the present water quality status (Olsson et al., 2009).
Groundwater quality models can simulate among others: • Groundwater ages, • Species transport, • Propagation of mineral dissolution and precipitation fronts, • Mineral buffering during acid mine drainage, • Cation exchange, • NAPL dissolution, • BTEX degradation and corresponding geochemical changes, • Temperature-dependent pyrite oxidation during deep well injections, • Natural attenuation of ammoniacal liquor: Phenol degradation, nitrification and ion exchange of ammonium, • Seawater intrusion and mixing, • Fixed-pressure gas-phase equilibria, • Isotope mole balance, • any kinetically controlled reactions. www.intechopen.com Monitoring and Modelling of Water Quality

203
Atmospheric water quality models are usually parts of tools simulating air quality.In those models atmospheric water quality is simulated mostly as an element of • aerosols formation, • wet deposition.
In following tables are presented examples of modelling tools used for simulation of: • atmospheric water quality (Table 1), • surface water quality (Table 2), • ground water quality (Table 3), • surface-groundwater quality (Table 4).2010) is an upgrade that adds to the previous version the ability to specify timedependent sources and boundary conditions (without programming) and to output information pertaining to source and boundary condition nodes in a convenient format.The code employs a 2D or 3D finite-element and finite-difference method to approximate the governing equations that describe the two interdependent processes that are simulated: 1) Fluid-density-dependent saturated or unsaturated ground-water flow; and either 2) (a) transport of a solute in the ground water, in which the solute may be subject to: equilibrium adsorption on the porous matrix, and both first-order and zero-order production or decay; or (b) transport of thermal energy in the ground water and solid matrix of the aquifer.http://water.usgs.gov/nrp/gwsoftware/sutra/sutra.html/ US Geological Survey (Free) (Voss, Provost, 2010) GMS -Groundwater Modeling System GMS provides tools for every phase of a groundwater simulation including site characterization, model development, calibration, post-processing, and visualization.GMS supports both finite-difference and finite-element models in 2D and 3D including MODFLOW 2000, MODPATH, MT3DMS/RT3D, SEAM3D, ART3D, UTCHEM, FEMWATER, PEST, UCODE, MODAEM and SEEP2D.GMS can be used for simulation of:

Examples of use of integrated systems for water quality monitoring and modelling
In this section two examples of integrated real-time monitoring and modelling systems are presented.Both systems are up-to-date (are being still developed under ongoing projects).Both are also aimed at providing managers with additional information about the environment, information needed for efficient operation.First of mentioned systems is the system for feedback-driven in-situ remediation developed in the UPSOIL project (Sustainable Soil Upgrading by Developing Cost effective, Biogeochemical Remediation Approaches) (UPSOIL, 2011).The second is system developed in the ZiZOZap project, aimed at supporting the management and protection of dammed reservoir (ZiZOZap, 2011).

Monitoring-modelling system for in-situ chemical oxidation
One of the UPSOIL project test sites (used here as an example) was located in an industrial area at the port in Belgium.Until 2001 a warehouse for non-hazardous (no soil polluting) goods was located on this site.Since 2002 the storage of hazardous products (acetone, isopropyl alcohol, methyl ethyl ketone, vinyl acetate, acrylates, ethyl acetate, fatty acids, acetic acid) was started on the site.Contaminants present at the site included: heavy metals, mineral oil, polycyclic aromatic hydrocarbons, volatile organic compounds, benzene, toluene, xylene, extractable organic halogen, oils and grasses, trichloroethylene and total organic carbon.
The remediation process was based on the optimal interaction between the injected remedial agents and the target contaminants.The first version of the injection system (MIP-IN) was a combination of the commercially available Geoprobe MIP system for in-situ detection of volatile contaminants and a system for in situ injection of remediation liquids into the soil.The system, for 12 months was under iterative "modification -evaluation" process, incorporating suggestions and technical requirements defined by the stakeholders involved within project.
The whole "contaminant detection -injection cycle" encompasses the following scheme: www.intechopen.com

•
Volatile contaminants enter the MIP device and are detected over 0.3 m vertical soil column.
• App. 25 samples from each 0.3 m depth interval are transported by the carrier gas to the field Gas Chromatograph (GC) which is giving a very high data resolution of the contaminant spreading.

•
The field GC signal from the 0.3 m interval and correlating depth interval is shown on the interface.The MIP signal response is logged automatically.
• When contamination is detected the operator has to define a balanced volume of solution to be injected at the corresponding 0.3 m interval.The volume to be injected is entered on the laptop and the program automatically gives a signal to inject this volume when the injection part of the probe is at the same depth as the corresponding MIP signal.
• Under pressure the injection pump delivers at a defined flow rate the volume of solution defined for a given depth interval.Pressure, flow rate and injected volume are logged automatically.

•
The solution is entering the soil under pressure where it is spread due to the geological settings.
Real-time monitoring system used in this test site included 14 monitoring wells, which were equipped with sensors logging values of pH, redox, temperature and conductivity with 15minutes intervals (Fig. 6).This system was established before the injections.It operated for four months after the injection and during the field work it was a complement to the measurements done with the gas chromatograph coupled with a system for in-situ injection.Apart from real-time monitoring system, six sampling campaigns were done and key physical and chemical parameters were measured in each monitoring well.Samples were taken 17 weeks before injection (campaign T0b), 1 week before injection (T0a), 1 week after injection (T1), 3 weeks after injection (T2), 8 weeks after injection (T3) and 16 weeks after injection (T4).
During this remediation test a mathematical transport model was developed to enable optimal designing of the injection process as well as the re-arranging the whole procedure after the first step of the remediation (e.g.add new wells, change the volume of oxidants).Within the UPSOIL project relatively simple and operational software was developed for preliminary site specific design and further optimisation of the injection.In addition, during and after the injection field work this software serves additionally as a tool gathering all the field data including the real-time logged parameters (like pH, temperature, oxidationreduction potential, conductivity) and the chemical data measured periodically during the sampling campaigns.The model consists of the Excel-Python module for calculations of physical parameters of the injection, and PhreeqC based module for hydro-geochemical simulations.The outcome of the first part of the model (physical module) includes: suggested radius of influence (ROI), • total bulk treatment volume, • total volume of reactant to be delivered, • maximum volume of oxidant required at each injection interval, • duration of injected oxidant effectiveness, • effective velocity of the groundwater, • injection time to reach the suggested ROI, • suggested number of injection wells in the treatment area, • suggested injection depth intervals to be used, • suggested concentration of oxidant to be used (at averaged amounts of pollutants + natural demand).
The physical module of the model can be used to define the optimal injection strategy before moving into the field.Later, during the injection field work additional site specific data can be gradually inserted into the model in order to observe the soil absorption capacity (actual volume of liquid that can be injected at a given depth interval at a reasonable flow and with no "surface break through") and radius of influence at a given injection volume and flow/pressure rate.
In combination with the physical module (Excel-Python application) a 1D transport and chemical reactions module was elaborated for the oxidation processes (permanganate as an oxidant) using the PhreeqC code.This model requires input data including: parameters of the liquid to be injected, the baseline geochemistry (situation before injection) and the concentrations levels and type of contamination in the soil.The objective of the transport and chemical model is to simulate the chemical response to the injection and predict when (if required) it would be optimal to carry out next injection campaign.The prediction is gradually more solid when field monitoring data after injection are put into the model.Thanks to the continuously updated database of the developed tool it is possible to get actual comparisons of results derived from loggers, chemical monitoring and numerical modelling.
During the field works, at 3 points (Fig. 6) 435 kg NaMnO4 in 5.2 m³ of water was injected at a depth between 2 and 7 m below ground level.Successful reaching of targeted interval by oxidant was observed via: • visual detection of the purple colour in monitoring wells, • significant decrease of the oxidation-reduction potential • increase in electric conductivity.
Results of the remediation are shown also as an example of benzene concentrations before and after the injections (Fig. 7).

Monitoring-modelling system for the dam reservoir management and protection
The ZiZOZap project is a part of the efforts to develop numerical multidimensional models of water reservoirs, which are undertaken in leading world countries.These models facilitate management of reservoir for their ability to predict the effects of the decisions undertaken.The purpose is to enhance the environmental safety and public heath of local population exploiting water resources.The object of the project study, Goczalkowice Water Reservoir, is a crucial water resource for 3,5 millions of inhabitants of Upper Silesia region (southern Poland).The Reservoir is also a unique natural area -a habitat for number of valuable species of birds, mammals, fish, small invertebrates and plants.Accommodation of environmental values and human needs in the area of The Reservoir is one of major tasks of the project.
The model which will be obtained as a result of the project will support the process of decision making and management of the Reservoir.Moreover, the model after necessary adaptations should be applicable for other water reservoirs (IPIS, 2011).
For the case study reservoir a monitoring and analyses of various environmental elements are carried out by interdisciplinary groups of experts.Data on hydrological, hydrogeological and physico-chemical conditions of water and bottom sediments as well as parameterised ecological and hygienic indicators referring to fauna, flora and the natural environment around the reservoir are collected in integrated databases.Project partners try to identify the key issues related to optimal management of the dam reservoir and build an information system together with a database.Based on the obtained research results and water management scenarios a numeric model of the reservoir is being developed.This will allow continuous assessment of the quality and functional state of the reservoir as well as stimulation and forecast of its changes.It is expected that in practice the system of reservoir models will enable to predict qualitative and quantitative changes in water resources which will affect water treatment and minimisation of costs, as well as forecasting water fertility and changes in the reservoir or the surrounding ecosystems (IETU, 2010).
As a part of created modelling system, a model for reservoir hydrodynamics and ecosystems was developed using ELCOM and CAEDYM software.ELCOM (Estuary, Lake and Coastal Ocean Model) is a three-dimensional hydrodynamics model for lakes and reservoirs, and is used to predict the variation of water temperature and salinity in space and time.The model forms the three-dimensional hydrodynamics driver to the CAEDYM water quality model (Hodges & Dallimore, 2009).The CAEDYM (Computational Aquatic Ecosystem Dynamics Model) is an aquatic ecological model that consists of a series of mathematical equations representing the major biogeochemical processes influencing water quality.At its most basic, CAEDYM is a set of library subroutines that contain process descriptions for primary production, secondary production, nutrient and metal cycling, and oxygen dynamics and the movement of sediment (Hipsey et al., 2009;Hipsey, 2009).
Within the ZiZOZap project the integrated ELCOM-CAEDYM model was coupled with mentioned above databases, which are used for storing the periodically collected and realtime measured data.Monitoring database includes among others: • Real-time measured parameters: inflow (main river, pumping stations), outflows, water intake, water conductivity, pH, water temperature (at 1m depth intervals), dissolved oxygen, chlorides, nitrates, chlorophyll, redox potential, turbidity, air temperature, wind speed and direction, air humidity, air pressure, precipitation, solar radiation.

Conclusions
General conclusions of this chapter are as follow: • Monitoring of the water quality (for atmospheric water, surface water and groundwater) should be designed in a way: • Ensuring spatial and temporal comparisons of the results -It is possible only if the monitoring is integrated in time and space, and if the structure of the monitoring system is uniform in all monitoring points.
• Addressing local and regional problems.
• Results of the monitoring should be stored in a form allowing their immediate use (e.g. as online databases).
• If there are no resources or technical/environmental possibilities for monitoring of needed water quality parameters, appropriate models should be used.Models can be coupled for this purpose with monitoring systems including simple parameters, directly related to the water quality.
• Each short and long-term activities potentially affecting the water quality should be preceded by detailed analyses of different scenarios and their impacts.For such tasks a set of widely used modelling tools is easily available.

Fig. 1 .
Fig. 1.Block diagram of the evaluation of surface water status, according to the Water Framework Directive (after: Loga and Sawicka, 2009)

Fig. 5 .
Fig. 5. Scheme of automatic collector for sampling the atmospheric precipitation: 1 -cover, 2 -electric motor, 3 -polyethylene funnel, 4 -filtration funnel, 5 -polyethylene bottle for collecting filtrate, 6 -humidity sensor.Samplers should be placed ca.1.5 m above the ground, in an open area, at best, overgrown with grass.The detailed conditions for collector location are given in the Polish standard (PN-ISO 5667-8), which is a translation, without any changes of the international standardISO 5667-8:1993 (ISO, 1993).

Fig. 6 .
Fig. 6.Location of the 3 MIP-IN injection points and 14 monitoring points Sample output from the ELCOM model (water velocity at different weather and inflow conditions) is presented on Figure 8. Example of output from the CAEDYM model (dissolver oxygen, temperature) is shown on the Figure 9.

Fig. 8 .
Fig. 8. Sample output from the ELCOM model for Goczalkowice Reservoir (velocities distribution) The State Environmental Monitoring of surface water in Poland is led by the Voivodship Inspectorates for Environmental Protection, and coordinated by the Main Inspectorate for Environmental Protection.The detailed plans of sampling campaigns, carried out in a frame of surface water monitoring, might be found in Monitoring of Environment Programmes, which are available on the website of Voivodship Inspectorate for Environmental Protection.In 2009, the number of monitoring points was 1616 and they were localised within 1328 homogeneous surface water bodies.
II class -water of good quality -values of some parameters are increased, what is caused only by natural factors.Hence, the chemical status of water is the result of geogenic processes and human impact is negligible, • III class -water of satisfactory quality.Values of several parameters are increased mainly as a result of natural processes.However, changes in chemical composition might reflect a feeble human impact, •

Table 2 .
Models for simulation of surface water quality l a y e r s ) .M o d e l c a n b e u s e d t o a s s e s s t h e l o n g -t e r m annual mean deposition of reduced and oxidised nitrogen and sulphur.FRAME was developed initially to focus in particular on transport and deposition of reduced nitrogen and was named the Fine Resolution AMmonia Exchange model.Recent developments in the treatment of sulphur and oxidised nitrogen mean that it may now be considered as a robust multi-chemical species tool.http://www.frame.ceh.ac.uk/ / www.intechopen.comhttp://www.iiasa.ac.at/rains/documentation.html?sb=11 / International Institute for Applied Systems Analysis (Amann et al., 2004) Table 1.Models for simulation of atmospheric water quality www.intechopen.comwww.intechopen.comwww.intechopen.comwww.intechopen.com

Table 3 .
Models for simulation of groundwater quality www.intechopen.com

Table 4 .
Models for simulation of surface and groundwater quality